Introduction to Google Professional Cloud Architect Exam

Google Professional Cloud Architect Exam is a certification exam that is conducted by Google to validates candidate knowledge and skills of working as a Professional Cloud Architect in the IT industry.

After passing this exam, candidates get a certificate from Google that helps them to demonstrate their proficiency in Google Professional Cloud Architect to their clients and employers.

Section #6. Improving and validating the reliability of processes and solutions

The final exam domain is compact and throws light on concepts like deployment & release management, evaluations of quality control measures, monitoring and logging solutions, and helping users through deployed aids for the same.

Reference: https://cloud.google.com/certification/cloud-architect

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Managing & Provisioning Solution Infrastructures

• Configure network topologies: the examinees should have the ability to extend to hybrid and on-premises networking and multi-Cloud environment that may entail GCP to GCP communication. It also requires their understanding of data protection and security;
• Configure compute systems: you should understand system provisioning; compute volatility configuration; container orchestration using Kubernetes; technology configuration for infrastructure provisioning; network configuration for the compute nodes.
• Configure individual storage systems: the areas of focus should include data storage allocation; access management and security; data processing and compute provisioning; data lifecycle management and data retention; network configuration for the data latency and transfer;

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Topics of Google Professional Cloud Architect Exam

Candidates must know the exam topics before they start of preparation. because it will really help them in hitting the core. Our Google Professional Cloud Architect Dumps will include the following topics:

1. Designing and planning a cloud solution architecture

Business requirements considerations

• Design decision trade-offs
• Cost optimization
• Business use cases and product strategy
• Compliance and observability
• Integration with external systems
• Build, buy or modify
• Movement of data
• Success measurements (e.g., key performance indicators [KPI], return on investment [ROI], metrics)
• Supporting the application design

Technical requirements considerations

• High availability and failover design
• Scalability to meet growth requirements
• Performance and latency
• Elasticity of cloud resources

Network, Storage, and Compute resources Considerations

• Choosing data processing technologies
• Integration with on- premises/multi- cloud environments
• Choosing compute resources (e.g., preemptible, custom machine type, specialized workload)
• Cloud-native networking (VPC, peering, firewalls, container networking)
• Choosing appropriate storage types (e.g., object, file, RDBMS, NoSQL, NewSQL)
• Mapping compute needs to platform products

Creating a migration plan

• Testing and proof of concept
• Network planning
• Dependency management planning
• Integrating solution with existing systems
• Licensing mapping
• Migrating systems and data to support the solution

Envisioning future solution improvements

• Cloud and technology improvements
• Business needs evolution
• Evangelism and advocacy

2. Managing and provisioning a solution Infrastructure

Configuring network topologies

• Security and data protection
• Extending to on-premises (hybrid networking)
• Extending to a multi-cloud environment that may include GCP to GCP communication

Configuring individual storage systems

• Data retention and data life cycle management
• Security and access management
• Data growth management
• Network configuration for data transfer and latency
• Data processing/compute provisioning
• Data storage allocation

Configuring compute systems

• Container orchestration with Kubernetes
• Compute system provisioning
• Network configuration for compute nodes
• Compute volatility configuration (preemptible vs. standard)
• Infrastructure provisioning technology configuration (e.g. Chef/Puppet/Ansible/Terraform/Deployment Manager)

3. Designing for security and compliance

Security considerations

• Penetration testing
• Separation of duties (SoD)
• Identity and access management (IAM)
• Managing customer- managed encryption keys with Cloud KMS
• Data security (key management, encryption)
• Security controls (e.g., auditing, VPC Service Controls organization policy)
• Resource hierarchy (organizations, folders, projects)

compliance Considerations

• Commercial (e.g., sensitive data such as credit card information handling, personally identifiable information [PII])
• Audits (including logs)
• Legislation (e.g., health record privacy, children's privacy, data privacy, and ownership)
• Industry certifications (e.g., SOC 2)

4. Analyzing and optimizing technical and business processes

Analyzing and defining technical processes considerations

• Service catalog and provisioning
• Testing and validation
• Troubleshooting / post mortem analysis culture
• Software development life cycle plan (SDLC)
• Continuous integration / continuous deployment
• Business continuity and disaster recovery

Analyzing and defining business processes. Considerations include:

• Team assessment / skills readiness
• Cost optimization / resource optimization (capex / opex)
• Change management
• Decision- making process
• Stakeholder management (e.g. influencing and facilitation)
• Customer success management

Developing procedures to ensure resilience of solution in production (e.g., chaos engineering)

5. Managing implementation

Advising development/operation team(s) to ensure successful deployment of the solution. considerations

• Application development
• Testing frameworks (load/unit/integration)
• API best practices
• Data and system migration tooling

Interacting with Google Cloud using GCP SDK (gcloud, gsutil, and bq) considerations

• Local installation
• Google Cloud Shell

6. Ensuring solution and operations reliability

• Monitoring/logging/profiling/alerting solution
• Assisting with the support of solutions in operation
• Deployment and release management
• Evaluating quality control measures

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